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Ad-hoc information retrieval refers to the task of returning information resources related to a user query formulated in natural language.

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Latest papers without code

Neural document expansion for ad-hoc information retrieval

27 Dec 2020

Recently, Nogueira et al. [2019] proposed a new approach to document expansion based on a neural Seq2Seq model, showing significant improvement on short text retrieval task.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

A White Box Analysis of ColBERT

17 Dec 2020

Transformer-based models are nowadays state-of-the-art in ad-hoc Information Retrieval, but their behavior is far from being understood.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

Investigating Retrieval Method Selection with Axiomatic Features

11 Apr 2019

We consider algorithm selection in the context of ad-hoc information retrieval.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

Fidelity-Weighted Learning

ICLR 2018

To this end, we propose "fidelity-weighted learning" (FWL), a semi-supervised student-teacher approach for training deep neural networks using weakly-labeled data.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

MatchZoo: A Toolkit for Deep Text Matching

23 Jul 2017

In recent years, deep neural models have been widely adopted for text matching tasks, such as question answering and information retrieval, showing improved performance as compared with previous methods.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL QUESTION ANSWERING TEXT MATCHING

Topical Coherence in LDA-based Models through Induced Segmentation

ACL 2017

This paper presents an LDA-based model that generates topically coherent segments within documents by jointly segmenting documents and assigning topics to their words.

AD-HOC INFORMATION RETRIEVAL CLASSIFICATION INFORMATION RETRIEVAL TOPIC MODELS

DE-PACRR: Exploring Layers Inside the PACRR Model

27 Jun 2017

Recent neural IR models have demonstrated deep learning's utility in ad-hoc information retrieval.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL

Toward a Deep Neural Approach for Knowledge-Based IR

23 Jun 2016

With this in mind, we argue that embedding KBs within deep neural architectures supporting documentquery matching would give rise to fine-grained latent representations of both words and their semantic relations.

DOCUMENT RANKING INFORMATION RETRIEVAL